ACML2010  

Accepted Posters

Poster abstracts (pdf)

Poster panel size: 165cm (height) x 110cm (width)

P01: Utilizing Fuzzy-SVM and a Subject Database to Reduce the Calibration Time of P300-based BCI
Sercan Taha Ahi, Tokyo Institute of Technology; Natsue Yoshimura, Tokyo Institute of Technology; Hiroyuki Kambara, Tokyo Institute of Technology; Yasuharu Koike, Tokyo Institute of Technology

P02: Feature Selection for Reinforcement Learning: Evaluating Implicit State-reward Dependency via Conditional Mutual Information
Hirotaka Hachiya, Tokyo Institute of Technology; Masashi Sugiyama, Tokyo Institute of Technology

P03: Dependence Minimizing Regression with Model Selection for Non-linear Causal Inference under Non-Gaussian Noise
Makoto Yamada, Tokyo Institute of Technology; Masashi Sugiyama, Tokyo Institute of Technology

P04: Joint Unsupervised Learning of Parallel Sequence Alignment and Segmentation
Mark Fishel, University of Tartu

P05: Multi-class Subgroup Discovery
Tarek Abudawood, University of Bristol; Peter Flach, University of Bristol

P06: A Comparison of CNF with CRF in Named Entity Recognition Task
Kei Uchiumi, Yahoo Japan Corporation; Keigo Machinaga, Yahoo Japan Corporation; Toshiyuki Maezawa, Yahoo Japan Corporation; Toshinori Satou, Yahoo Japan Corporation

P07: Multiscale-bagging with Applications to Classification
Masayoshi Aoki, Tokyo Institute of Technology; Takafumi Kanamori, Nagoya University; Hidetoshi Shimodaira, Tokyo Institute of Technology

P08: Contrasting Correlations by an Efficient Double-clique Search Method
Aixiang Li, Hokkaido University; Makoto Haraguchi, Hokkaido University

P09: Model-induced Regularization
Shinichi Nakajima, Nikon Corporation; Masashi Sugiyama, Tokyo Institute of Technology

P10: Slice Sampling on Chinese Restaurant Process
Takaki Makino, University of Tokyo

P11: Interactive Behavior Adaptation through Dialogue Based on Bayesian Network
Saifuddin Md. Tareeq, The Graduate University for Advanced Studies; Tetsunari Inamura, National Institute of Informatics

P12: Maximum Volume Clustering
Gang Niu, Nanjing University; Bo Dai, Chinese Academy of Science; Lin Shang, Nanjing University; Masashi Sugiyama, Tokyo Institute of Technology

P13: Using Conditional Random Fields to Validate Observations in a 4W1H Paradigm
Leon F. Palafox, University of Tokyo; Laszlo A. Jeni, University of Tokyo; Hideki Hashimoto, University of Tokyo

P14: Multiscale Bagging with Applications to Classification and Active Learning
Hidetoshi Shimodaira, Tokyo Institute of Technology; Takafumi Kanamori, Nagoya University; Masayoshi Aoki, Tokyo Institute of Technology; Kouta Mine, Tokyo Institute of Technology

P15: Adjustment for Multiple Hypotheses Testing in Comparative Classification Studies
Daniel Berrar, Tokyo Institute of Technology

P16: Inference in Latent Conditional Models: The Computational Complexity Analysis and a Comparative Study of Solutions
Xu Sun, University of Tokyo; Hisashi Kashima, University of Tokyo; Takuya Matsuzaki, University of Tokyo

P17: Improving Graph-based Semi-supervised Learning by Feature Space Transformation
Yu-Shi Lin, Academia Sinica and National Taiwan University; Chun-Nan Hsu, Academia Sinica and University of Southern California

P18: Image Annotation via Multi-instance Learning with Pyramid Graph Kernel
Zhi Nie, Tsinghua University; Guiguang Ding, Tsinghua University; Chunping Li, Tsinghua University

P19: Proximity in Large Bipartite Graphs with Unsupervised Auxiliary Information
Rudy Raymond, IBM Research - Tokyo; Yuta Tsuboi, IBM Research - Tokyo; Hisashi Kashima, The University of Tokyo; Issei Sato, The University of Tokyo